Klucik Josef, Xiao Yun-De, Hammond Phillip S, Harris Rebecca, Schmitt Jeffrey D
Targacept Inc., 200 East First Street, Suite 300, Winston-Salem, NC 27101, USA.
J Med Chem. 2004 Dec 30;47(27):6831-9. doi: 10.1021/jm049729z.
Targacept active conformation search (TACS) is a novel variation of well-established three-dimensional quantitative structure--activity relationship methodologies that seeks to determine probable conformation(s) of ligands bound to their protein targets. A combination of affinity or activity data and energetically accessible conformational ensembles, each conformer described by three-dimensional (3-D) sensitive descriptors, forms the basis of the TACS data model. Recursive pruning is used to reduce the size of both the conformational ensemble and the descriptor space until the TACS data model contains just enough information to determine probable conformation(s) of ligands bound to their protein targets. The TACS algorithm is comprised of five components: (1) conformational ensemble generation, (2) 3-D sensitive descriptor calculation, (3) ensemble descriptor preprocessing, (4) model generation, and (5) prediction of bound conformation(s). Significantly, this method precludes the need for subjective or objective molecular alignment. We report the application of this technique to five benchmark protein-ligand couples where the conformation of a bound ligand has been previously established using X-ray crystallography: 9-cis-retinoic (1) and 9-trans-retinoic acid (2), both agonists for the retinoic acid receptor gamma, compounds KH1060 (3) and MC1288 (4), which bind to the vitamin D3 receptor, and R04 (5), an inhibitor bound to human rhinovirus 14 thermolysin. The binding conformations predicted by TACS were compared to the crystallographic structures extracted from their respective binding sites using root-mean-squared deviation (rmsd) criteria. Three of the conformations found using TACS were within crystallographic error. 9-cis-Retinoic acid, 9-trans-retinoic acid, and MC1288, when superimposed on their crystallographic structures, gave rmsd values of 0.22, 0.17, and 0.34 A, respectively. The rmsd values for KH1060 (1.54 A) and R04 (1.01 A) were larger but still reasonable.
Targacept活性构象搜索（TACS）是一种成熟的三维定量构效关系方法的新颖变体，旨在确定与蛋白质靶点结合的配体的可能构象。亲和力或活性数据与能量上可及的构象集合（每个构象由三维（3-D）敏感描述符描述）的组合构成了TACS数据模型的基础。递归剪枝用于减小构象集合和描述符空间的大小，直到TACS数据模型包含足够的信息来确定与蛋白质靶点结合的配体的可能构象。TACS算法由五个部分组成：（1）构象集合生成，（2）3-D敏感描述符计算，（3）集合描述符预处理，（4）模型生成，以及（5）结合构象预测。值得注意的是，该方法无需主观或客观的分子比对。我们报告了该技术在五个基准蛋白-配体对中的应用，其中结合配体的构象先前已通过X射线晶体学确定：9-顺式视黄酸（1）和9-反式视黄酸（2），均为视黄酸受体γ的激动剂，化合物KH1060（3）和MC1288（4），它们与维生素D3受体结合，以及R04（5），一种与人鼻病毒14嗜热菌蛋白酶结合的抑制剂。使用均方根偏差（rmsd）标准将TACS预测的结合构象与从各自结合位点提取的晶体结构进行比较。使用TACS找到的三个构象在晶体学误差范围内。9-顺式视黄酸、9-反式视黄酸和MC1288叠加在其晶体结构上时，rmsd值分别为0.22、0.17和0.34 Å。KH1060（1.54 Å）和R04（1.01 Å）的rmsd值较大但仍合理。
